Blockchain is an emerging technology that has recently been the focus for </span><span style="font-family:Verdana;">many researchers who have highlighted its diverse applications including</sp...Blockchain is an emerging technology that has recently been the focus for </span><span style="font-family:Verdana;">many researchers who have highlighted its diverse applications including</span><span style="font-family:Verdana;"> healthcare. Transparency in managing unsolicited patient complaints is important in healthcare for both patients and healthcare providers;in addition, patient complaints analysis is significant to the continued quality improvement. Accordingly, the purpose of this study is to understand the nature of patient complaints management in the healthcare settings, explore the implications of blockchain on the management of patient complaints, and identify limitations in the usage of blockchain. Structured qualitative review and content analysis of the literature methods were used through multiple inclusion and exclusion phases for the scope of this research. Blockchain technology characteristics have been analyzed and approximated with desired features in the patients’ complaint management. Patient complaints provide valuable information to drive continuous improvements in healthcare</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">.</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> Blockchain is described as transparent, decentralized, immutable and anonymous. Results of this research found that a complaint Management system that is built on blockchain technology might have desired features that involve data integrity, security and transparency. Blockchain does have certain limitations that involve cybersecurity, scalability, confidentiality, readiness to adopt it, and </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">is </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">uncertainty about its impact. As a conclusion, </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">i</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">mplementing a system to </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">manage patient complaints that </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">is</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> based on blockchain technology is promising, due to its desired possible features.展开更多
In the recent years spam became as a big problem of Internet and electronic communication. There developed a lot of techniques to fight them. In this paper the overview of existing e-mail spam filtering methods is giv...In the recent years spam became as a big problem of Internet and electronic communication. There developed a lot of techniques to fight them. In this paper the overview of existing e-mail spam filtering methods is given. The classification, evaluation, and comparison of traditional and learning-based methods are provided. Some personal anti-spam products are tested and compared. The statement for new approach in spam filtering technique is considered.展开更多
Recently the number of undesirable messages coming to e-mail has strongly increased. As spam has changeable character the anti-spam systems should be trainable and dynamical. The machine learning technology is success...Recently the number of undesirable messages coming to e-mail has strongly increased. As spam has changeable character the anti-spam systems should be trainable and dynamical. The machine learning technology is successfully applied in a filtration of e-mail from undesirable messages for a long time. In this paper it is offered to apply Case Based Reasoning technology to a spam filtering problem. The possibility of continuous updating of spam templates base on the bases of which new coming spam messages are compared, will raise efficiency of a filtration. Changing a combination of conditions it is possible to construct flexible filtration system adapted for different users or corporations. Also in this paper it is considered the second approach as implementation of CRM technology to spam filtration which is not applied to this area yet.展开更多
文摘Blockchain is an emerging technology that has recently been the focus for </span><span style="font-family:Verdana;">many researchers who have highlighted its diverse applications including</span><span style="font-family:Verdana;"> healthcare. Transparency in managing unsolicited patient complaints is important in healthcare for both patients and healthcare providers;in addition, patient complaints analysis is significant to the continued quality improvement. Accordingly, the purpose of this study is to understand the nature of patient complaints management in the healthcare settings, explore the implications of blockchain on the management of patient complaints, and identify limitations in the usage of blockchain. Structured qualitative review and content analysis of the literature methods were used through multiple inclusion and exclusion phases for the scope of this research. Blockchain technology characteristics have been analyzed and approximated with desired features in the patients’ complaint management. Patient complaints provide valuable information to drive continuous improvements in healthcare</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">.</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> Blockchain is described as transparent, decentralized, immutable and anonymous. Results of this research found that a complaint Management system that is built on blockchain technology might have desired features that involve data integrity, security and transparency. Blockchain does have certain limitations that involve cybersecurity, scalability, confidentiality, readiness to adopt it, and </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">is </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">uncertainty about its impact. As a conclusion, </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">i</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">mplementing a system to </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">manage patient complaints that </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">is</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> based on blockchain technology is promising, due to its desired possible features.
文摘In the recent years spam became as a big problem of Internet and electronic communication. There developed a lot of techniques to fight them. In this paper the overview of existing e-mail spam filtering methods is given. The classification, evaluation, and comparison of traditional and learning-based methods are provided. Some personal anti-spam products are tested and compared. The statement for new approach in spam filtering technique is considered.
文摘Recently the number of undesirable messages coming to e-mail has strongly increased. As spam has changeable character the anti-spam systems should be trainable and dynamical. The machine learning technology is successfully applied in a filtration of e-mail from undesirable messages for a long time. In this paper it is offered to apply Case Based Reasoning technology to a spam filtering problem. The possibility of continuous updating of spam templates base on the bases of which new coming spam messages are compared, will raise efficiency of a filtration. Changing a combination of conditions it is possible to construct flexible filtration system adapted for different users or corporations. Also in this paper it is considered the second approach as implementation of CRM technology to spam filtration which is not applied to this area yet.
